Shifts in meteorological variables due to changing climate potentially affect a wide range of human activities. Key impacts of concern can be of short temporal duration (sub-annual), manifest themselves over fine spatial scales (sub-national), and affect different biophysical endpoints with distinct consequences for different economic activities – even those within the same broad economic sector (e.g., yield responses that differ by crop). These characteristics make it especially challenging for integrated assessment models (IAMs) to simulate the societal consequences climate impacts, as the relevant processes occur at a finer level of temporal, spatial and sectoral granularity than IAMs are equipped to represent. Moreover, process simulation of impact pathways' temporal, spatial and sectoral details is computationally intractable unless the domain of analysis is restricted to a few key subsystems. Given this state of affairs there is tremendous interest in the development of computationally efficient emulators of the responses of human activities to climate change impacts, and the methods for linking them to IAMs. A flurry of recent empirical research has highlighted the possibilities of constructing emulators from reduced-form statistical models estimated on observed human system responses to weather shocks. My talk will give a practical example of the construction of such an emulator and the integration of its results within an economic model to assess the impact of climate change on the US electric power sector. A crucial element of this approach is the specification of the climatic shock to human systems, which is typically achieved by forcing the statistical response surface with transformed outputs of global climate model (GCM) simulations of warming scenarios. This represents an important branch point in impact assessment, as calculations downstream of this point are then locked in to the particular GCM-climate scenario combinations used to specify the shocks. Circumventing this hysteresis requires the development of GCM emulators which are capable of generating fine temporal and spatial scale fields of key meteorological variables using as inputs the global mean temperature changes computed by IAMs' stylized 1-D climate sub-models. The talk will conclude with a discussion of potential approaches, and progress toward this goal.